Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films
The double-stranded B-form and A-form have long been considered the two most important native forms of DNA, each with its own distinct biological roles and hence the focus of many areas of study, from cellular functions to cancer diagnostics and drug treatment. Due to the heterogeneity and sensitivi...
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| Format: | Article |
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MDPI AG
2021-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/13/5895 |
| _version_ | 1797528825805930496 |
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| author | Kristina Serec Sanja Dolanski Babić |
| author_facet | Kristina Serec Sanja Dolanski Babić |
| author_sort | Kristina Serec |
| collection | DOAJ |
| description | The double-stranded B-form and A-form have long been considered the two most important native forms of DNA, each with its own distinct biological roles and hence the focus of many areas of study, from cellular functions to cancer diagnostics and drug treatment. Due to the heterogeneity and sensitivity of the secondary structure of DNA, there is a need for tools capable of a rapid and reliable quantification of DNA conformation in diverse environments. In this work, the second paper in the series that addresses conformational transitions in DNA thin films utilizing FTIR spectroscopy, we exploit popular chemometric methods: the principal component analysis (PCA), support vector machine (SVM) learning algorithm, and principal component regression (PCR), in order to quantify and categorize DNA conformation in thin films of different hydrated states. By complementing FTIR technique with multivariate statistical methods, we demonstrate the ability of our sample preparation and automated spectral analysis protocol to rapidly and efficiently determine conformation in DNA thin films based on the vibrational signatures in the 1800–935 cm<sup>−1</sup> range. Furthermore, we assess the impact of small hydration-related changes in FTIR spectra on automated DNA conformation detection and how to avoid discrepancies by careful sampling. |
| first_indexed | 2024-03-10T10:04:57Z |
| format | Article |
| id | doaj.art-bec799dbd2f640a5a6e47d0eb306f7a0 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T10:04:57Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-bec799dbd2f640a5a6e47d0eb306f7a02023-11-22T01:39:20ZengMDPI AGApplied Sciences2076-34172021-06-011113589510.3390/app11135895Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin FilmsKristina Serec0Sanja Dolanski Babić1Department of Physics and Biophysics, School of Medicine, University of Zagreb, 10000 Zagreb, CroatiaDepartment of Physics and Biophysics, School of Medicine, University of Zagreb, 10000 Zagreb, CroatiaThe double-stranded B-form and A-form have long been considered the two most important native forms of DNA, each with its own distinct biological roles and hence the focus of many areas of study, from cellular functions to cancer diagnostics and drug treatment. Due to the heterogeneity and sensitivity of the secondary structure of DNA, there is a need for tools capable of a rapid and reliable quantification of DNA conformation in diverse environments. In this work, the second paper in the series that addresses conformational transitions in DNA thin films utilizing FTIR spectroscopy, we exploit popular chemometric methods: the principal component analysis (PCA), support vector machine (SVM) learning algorithm, and principal component regression (PCR), in order to quantify and categorize DNA conformation in thin films of different hydrated states. By complementing FTIR technique with multivariate statistical methods, we demonstrate the ability of our sample preparation and automated spectral analysis protocol to rapidly and efficiently determine conformation in DNA thin films based on the vibrational signatures in the 1800–935 cm<sup>−1</sup> range. Furthermore, we assess the impact of small hydration-related changes in FTIR spectra on automated DNA conformation detection and how to avoid discrepancies by careful sampling.https://www.mdpi.com/2076-3417/11/13/5895DNA thin filmsFTIRB-form quantificationprincipal component analysis (PCA)support vector machine (SVM)principal component regression (PCR) |
| spellingShingle | Kristina Serec Sanja Dolanski Babić Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films Applied Sciences DNA thin films FTIR B-form quantification principal component analysis (PCA) support vector machine (SVM) principal component regression (PCR) |
| title | Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films |
| title_full | Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films |
| title_fullStr | Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films |
| title_full_unstemmed | Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films |
| title_short | Multivariate Analysis as a Tool for Quantification of Conformational Transitions in DNA Thin Films |
| title_sort | multivariate analysis as a tool for quantification of conformational transitions in dna thin films |
| topic | DNA thin films FTIR B-form quantification principal component analysis (PCA) support vector machine (SVM) principal component regression (PCR) |
| url | https://www.mdpi.com/2076-3417/11/13/5895 |
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